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Process Intelligence: The Next Leap Forward in Business Intelligence - and Intelligent Business

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Everything accomplished in an organization requires a series of business activities which together comprise a process. Whether the organization is a hospital, bank, manufacturer, or any other type of business, its level of success is directly tied to how well it performs and manages its many business processes.

However, today’s business intelligence (BI) and data discovery tools provide organizations with only the most basic insight into its processes – even critical business processes directly related to improving customer interactions and loyalty, building better quality products, mitigating risk, ensuring compliance and more. The key problem is BI tools generally do not provide analytics in the context of an overall business process. While BI and data discovery tools can provide point-in-time measures or key performance indicators for a given task, they cannot provide answers to such critical questions as:

  • What overall business process(es) is this task part of?
  • How does the performance of this task impact the other tasks within this process?
  • Is the performance quality and timeliness acceptable? If not, is the root cause due to problems with this task, or other tasks earlier in the process?
  • Is this task being performed each time the process is executed? If not, why not?

Business transformation and operational excellence cannot take place without answers to these questions. Those answers can only be found through a new, process intelligence-enabled BI platform that goes beyond other BI tools to provide a deeper, holistic understanding of the entire process and how the performance of each task affects other tasks.

Process intelligence is the next evolutionary step in BI that provides new, advanced capabilities essential to monitor, analyze, and improve an organization’s critical operational processes. No separate BPM or process modeling tools are required. It provides the ability to access and analyze data about individual instances of a process to monitor both effectiveness and compliance.

For example, a patient entering an emergency room is one discrete element in a process spanning multiple departments and systems of record. After arriving, triage is performed, after which the patient is assigned a room and then a doctor; evaluation and treatment occur; the patient can then be either admitted or discharged. Some sections of the process can be dynamically adjusted, such as when the triage process shows a patient is low priority and sent back to the waiting room. Other steps in the process may need to be strictly followed to ensure patient safety.

Clearly, an organization’s ability to manage each type of process and each individual process instance is directly related to its ability to understand exactly how processes are executed at various points in time, under different operating conditions. Unlike traditional BI solutions, a process intelligence-enabled BI platform will provide this deeper level of understanding, which in turn enables the discovery of new opportunities to optimize operational performance across virtually every industry, from healthcare providers to financial services companies and manufacturers.

There are three key benefits that a process intelligence-enabled BI platform delivers that today’s BI tools cannot match:

Understanding processes that span multiple operational systems. The complexity and diversity of real-world IT systems are the reasons why BI, BPM and process analysis technologies fall short. Process intelligence must be able to discover operational processes where individual process steps are executed on multiple back-end systems of record, and where no system of record or BPM technology provides central orchestration of the process – even when the process definition is either unknown to operations personnel or incorrectly documented. These challenges require the combination of a powerful data integration platform and a sophisticated process state engine. The combination of these technologies allows for the discovery and harvesting of data artifacts left behind in the multiple systems of record when any process is executed and manages the correlation of this data based on the process context.

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